Attractor-based trust-region algorithm for efficient training of multilayer perceptrons

A new training algorithm for multilayer perceptrons is proposed. The first phase is a trust region-based local search for fast training of networks. The second phase is an attractor-based global search for escaping local minima. Benchmark results show that the proposed algorithm outperforms previously reported existing techniques.